Rapid Vulnerability Assessment of Coastal Insular Ecosystems: Application to Algerian Islands
Abstract
Assessing the vulnerability of insular environments has become a major challenge in the context of increasing anthropogenic pressures and climate-change impacts. This study proposes a rapid environmental vulnerability assessment methodology, here applied to the best of the authors' knowledge in the international peer-reviewed literature to all Algerian coastal islands. The framework is based on a Global Vulnerability Index (GVI) integrating 21 ecological, socio-economic and environmental criteria, weighted using a hierarchical Analytic Hierarchy Process (AHP) with two levels (cluster and sub-criterion) to ensure that all pairwise comparison matrices satisfy Saaty's consistency threshold (CR < 0.10). This approach enables the prioritization of pressure levels affecting insular ecosystems using accessible data, while ensuring methodological robustness and reproducibility. A total of 36 representative insular sites were selected from 611 identified along the Algerian coastline and analyzed under five thematic scenarios: a balanced Normal scenario, plus Fishing, Tourism, Urbanization and Ecological-Sensitivity scenarios. The results were integrated into a Geographic Information System (GIS) to produce vulnerability maps. Spatial analysis highlights clear regional contrasts: marked heterogeneity in the western sector (GVI 0.21 – 0.80), more uniform vulnerability in the central sector driven by diffuse urbanization (GVI 0.40 – 0.51), and dominant fishing pressures in the eastern sector (GVI 0.36 – 0.56). A Monte-Carlo sensitivity analysis (±10 % and ±20 % perturbations of the AHP weights, 1 000 iterations) confirmed the robustness of the rankings (mean Spearman ρ > 0.98). A Chi-square goodness-of-fit test against a uniform distribution further confirmed that the GVI discriminates significantly between sites (χ² = 92.6, df = 4, p < 0.001). The methodology provides an operational decision-support tool for coastal management.